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Automated Machine Learning [[electronic resource] ] : Methods, Systems, Challenges / / edited by Frank Hutter, Lars Kotthoff, Joaquin Vanschoren
| Automated Machine Learning [[electronic resource] ] : Methods, Systems, Challenges / / edited by Frank Hutter, Lars Kotthoff, Joaquin Vanschoren |
| Autore | Hutter Frank |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2019 |
| Descrizione fisica | 1 online resource (XIV, 219 p. 54 illus., 45 illus. in color.) |
| Disciplina | 006.3 |
| Collana | The Springer Series on Challenges in Machine Learning |
| Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Artificial Intelligence Image Processing and Computer Vision Pattern Recognition |
| Soggetto non controllato |
Computer science
Artificial intelligence Optical data processing Pattern recognition |
| ISBN | 3-030-05318-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Hyperparameter Optimization -- 2 Meta-Learning -- 3 Neural Architecture Search -- 4 Auto-WEKA -- 5 Hyperopt-Sklearn -- 6 Auto-sklearn -- 7 Towards Automatically-Tuned Deep Neural Networks -- 8 TPOT -- 9 The Automatic Statistician -- 10 AutoML Challenges. |
| Record Nr. | UNINA-9910337835803321 |
Hutter Frank
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| Cham, : Springer Nature, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Discovery Science [[electronic resource] ] : 21st International Conference, DS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings / / edited by Larisa Soldatova, Joaquin Vanschoren, George Papadopoulos, Michelangelo Ceci
| Discovery Science [[electronic resource] ] : 21st International Conference, DS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings / / edited by Larisa Soldatova, Joaquin Vanschoren, George Papadopoulos, Michelangelo Ceci |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XXI, 482 p. 137 illus.) |
| Disciplina | 501 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Information storage and retrieval Application software Artificial Intelligence Data Mining and Knowledge Discovery Information Storage and Retrieval Computer Appl. in Social and Behavioral Sciences |
| ISBN | 3-030-01771-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Classification -- Meta-Learning -- Reinforcement Learning -- Streams and Time Series -- Subgroup and Subgraph Discovery -- Text Mining -- Applications. |
| Record Nr. | UNINA-9910349397603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Discovery Science [[electronic resource] ] : 21st International Conference, DS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings / / edited by Larisa Soldatova, Joaquin Vanschoren, George Papadopoulos, Michelangelo Ceci
| Discovery Science [[electronic resource] ] : 21st International Conference, DS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings / / edited by Larisa Soldatova, Joaquin Vanschoren, George Papadopoulos, Michelangelo Ceci |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XXI, 482 p. 137 illus.) |
| Disciplina | 501 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Information storage and retrieval Application software Artificial Intelligence Data Mining and Knowledge Discovery Information Storage and Retrieval Computer Appl. in Social and Behavioral Sciences |
| ISBN | 3-030-01771-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Classification -- Meta-Learning -- Reinforcement Learning -- Streams and Time Series -- Subgroup and Subgraph Discovery -- Text Mining -- Applications. |
| Record Nr. | UNISA-996466451503316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Learning and Intelligent Optimization [[electronic resource] ] : 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016, Revised Selected Papers / / edited by Paola Festa, Meinolf Sellmann, Joaquin Vanschoren
| Learning and Intelligent Optimization [[electronic resource] ] : 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016, Revised Selected Papers / / edited by Paola Festa, Meinolf Sellmann, Joaquin Vanschoren |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XI, 309 p. 74 illus.) |
| Disciplina | 005.1 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Computer science Artificial intelligence Computer science—Mathematics Discrete mathematics Computer simulation Computer Science Logic and Foundations of Programming Artificial Intelligence Discrete Mathematics in Computer Science Theory of Computation Computer Modelling |
| ISBN | 3-319-50349-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Learning a stopping criteria for Local Search -- Surrogate Assisted Feature Computation for Continuous Problems -- MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework -- Evolving Instances for Maximizing Performance Differences of State-of-The-Art Inexact TSP Solvers -- Extreme Reactive Portfolio (XRP): Tuning an Algorithm Population for Global Optimization -- Bounding the Search Space of the Population Harvest Cutting Problem with Multiple Size Stock Selection -- Designing and comparing multiple portfolios of parameter configurations for online algorithm selection -- Portfolios of Subgraph Isomorphism Algorithms -- Structure-preserving Instance Generation -- Feature Selection using Tabu Search with Learning Memory: Learning Tabu Search -- The Impact of Automated Algorithm Configuration on the Scaling Behaviour of State-of-the-art Inexact TSP Solvers -- Requests Management for Smartphone-based Matching Applications using a Multi-Agent Approach -- Self-Organizing Neural Network for Adaptive Operator Selection in Evolutionary Search -- Quantifying the Similarity of Algorithm Configurations -- Neighborhood synthesis from an ensemble of MIP and CP models -- Parallelizing Constraint Solvers for Hard RCPSP Instances -- Characterization of neighborhood behaviours in a multi-neighborhood local search algorithm -- Constraint Programming and Machine Learning for Interactive Soccer Analysis -- A Matheuristic Approach for the p-Cable Trench Problem -- An Empirical Study of Per-Instance Algorithm Scheduling -- Dynamic strategy to diversify search using history map in parallel solving -- Faster Model Based Optimization through Resource Aware Scheduling Strategies -- Risk-Averse Anticipation for Dynamic Vehicle Routing -- Solving GENOPT problems with the use of ExaMin solver -- Hybridisation of Evolutionary Algorithms through Hyper-heuristics for Global Continuous Optimisation. |
| Record Nr. | UNISA-996465494403316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Learning and Intelligent Optimization [[electronic resource] ] : 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016, Revised Selected Papers / / edited by Paola Festa, Meinolf Sellmann, Joaquin Vanschoren
| Learning and Intelligent Optimization [[electronic resource] ] : 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016, Revised Selected Papers / / edited by Paola Festa, Meinolf Sellmann, Joaquin Vanschoren |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XI, 309 p. 74 illus.) |
| Disciplina | 005.1 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Computer science Artificial intelligence Computer science—Mathematics Discrete mathematics Computer simulation Computer Science Logic and Foundations of Programming Artificial Intelligence Discrete Mathematics in Computer Science Theory of Computation Computer Modelling |
| ISBN | 3-319-50349-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Learning a stopping criteria for Local Search -- Surrogate Assisted Feature Computation for Continuous Problems -- MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework -- Evolving Instances for Maximizing Performance Differences of State-of-The-Art Inexact TSP Solvers -- Extreme Reactive Portfolio (XRP): Tuning an Algorithm Population for Global Optimization -- Bounding the Search Space of the Population Harvest Cutting Problem with Multiple Size Stock Selection -- Designing and comparing multiple portfolios of parameter configurations for online algorithm selection -- Portfolios of Subgraph Isomorphism Algorithms -- Structure-preserving Instance Generation -- Feature Selection using Tabu Search with Learning Memory: Learning Tabu Search -- The Impact of Automated Algorithm Configuration on the Scaling Behaviour of State-of-the-art Inexact TSP Solvers -- Requests Management for Smartphone-based Matching Applications using a Multi-Agent Approach -- Self-Organizing Neural Network for Adaptive Operator Selection in Evolutionary Search -- Quantifying the Similarity of Algorithm Configurations -- Neighborhood synthesis from an ensemble of MIP and CP models -- Parallelizing Constraint Solvers for Hard RCPSP Instances -- Characterization of neighborhood behaviours in a multi-neighborhood local search algorithm -- Constraint Programming and Machine Learning for Interactive Soccer Analysis -- A Matheuristic Approach for the p-Cable Trench Problem -- An Empirical Study of Per-Instance Algorithm Scheduling -- Dynamic strategy to diversify search using history map in parallel solving -- Faster Model Based Optimization through Resource Aware Scheduling Strategies -- Risk-Averse Anticipation for Dynamic Vehicle Routing -- Solving GENOPT problems with the use of ExaMin solver -- Hybridisation of Evolutionary Algorithms through Hyper-heuristics for Global Continuous Optimisation. |
| Record Nr. | UNINA-9910484319303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Metalearning : Applications to Automated Machine Learning and Data Mining
| Metalearning : Applications to Automated Machine Learning and Data Mining |
| Autore | Brazdil Pavel |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (349 pages) |
| Disciplina | 006.31 |
| Altri autori (Persone) |
van RijnJan N
SoaresCarlos VanschorenJoaquin |
| Collana | Cognitive Technologies |
| Soggetto topico |
Artificial intelligence
Data mining Machine learning |
| Soggetto non controllato |
Metalearning
Automating Machine Learning (AutoML) Machine Learning Artificial Intelligence algorithm selection algorithm recommendation algorithm configuration hyperparameter optimization automating the workflow/pipeline design metalearning in ensemble construction metalearning in deep neural networks transfer learning algorithm recommendation for data streams automating data science Open Access |
| ISBN | 3-030-67024-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464544803316 |
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Brazdil Pavel
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| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Metalearning : Applications to Automated Machine Learning and Data Mining
| Metalearning : Applications to Automated Machine Learning and Data Mining |
| Autore | Brazdil Pavel |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (349 pages) |
| Disciplina | 006.31 |
| Altri autori (Persone) |
van RijnJan N
SoaresCarlos VanschorenJoaquin |
| Collana | Cognitive Technologies |
| Soggetto topico |
Artificial intelligence
Data mining Machine learning |
| Soggetto non controllato |
Metalearning
Automating Machine Learning (AutoML) Machine Learning Artificial Intelligence algorithm selection algorithm recommendation algorithm configuration hyperparameter optimization automating the workflow/pipeline design metalearning in ensemble construction metalearning in deep neural networks transfer learning algorithm recommendation for data streams automating data science Open Access |
| ISBN | 3-030-67024-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910548277503321 |
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Brazdil Pavel
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| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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